A /29 subnet mask provides 8 total addresses, of which 6 are usable for hosts after excluding the network and broadcast addresses.

The space complexity of a recursive binary search is O(log n) due to the call stack.

The space complexity of a recursive binary search is O(log n) due to the call stack used for recursion.

The space complexity is O(log n) due to the recursive call stack.

A return value of -1 typically indicates that the searched element is not present in the array.

The space complexity of binary search is O(1) when implemented iteratively, as it uses a constant amount of space.

The worst-case number of iterations is log2(32) = 5.

The maximum number of comparisons needed is log2(16) = 4, but since we start counting from 0, it takes 5 comparisons.

In the worst case, binary search will make log2(16) = 4 comparisons.

In the worst case, binary search will take log2(16) = 4 comparisons, but since we start counting from 0, it will take 5 comparisons.

The maximum height of a binary tree occurs when the tree is skewed (like a linked list), resulting in a height of n.

The maximum height of a binary tree with 15 nodes occurs when the tree is skewed, which can have a height of 15.

The minimum number of nodes in a binary tree of height h is h + 1, which occurs in a skewed tree.

The maximum number of nodes in a binary tree of height h is 2^h - 1, which occurs in a complete binary tree.

In a binary tree, the maximum number of leaf nodes can be n, which occurs in a degenerate tree.

In a balanced binary tree, the maximum height is O(log n), as the tree is structured to minimize height.

If K=4 and there are 200 points, on average, each cluster will have 200/4 = 50 points assigned to it.

The network address is determined by the IP address and subnet mask; for 172.16.5.10/24, the network address is 172.16.5.0.

In a simple undirected graph, the maximum number of edges is given by the formula V(V-1)/2, which for 5 vertices is 5(5-1)/2 = 10.

Dijkstra's algorithm will perform at most V iterations, where V is the number of vertices. In this case, it will perform 5 iterations.

Using an adjacency matrix, the time complexity of Dijkstra's algorithm is O(V^2), which in this case is O(5^2) or O(25).

In a complete graph with V vertices, the maximum number of edges is given by V*(V-1)/2. For 5 vertices, it is 5*(5-1)/2 = 10.

In a simple undirected graph, the maximum number of edges is given by the formula V(V-1)/2. For 5 vertices, it is 5(5-1)/2 = 10.

In a simple undirected graph, the maximum number of edges is given by the formula V(V-1)/2, which for 5 vertices is 5(5-1)/2 = 10.

Dijkstra's algorithm will perform at most V iterations, where V is the number of vertices. In this case, it will perform 5 iterations.

DFS can detect cycles in a graph by keeping track of visited nodes and checking for back edges.

The Bellman-Ford algorithm can be used instead of Dijkstra's algorithm when the graph has negative edge weights, as it can handle such cases.

The Bellman-Ford algorithm can handle graphs with negative weight edges, unlike Dijkstra's algorithm.

The Bellman-Ford algorithm should be used instead of Dijkstra's algorithm when the graph has negative weight edges, as it can handle such cases.

The Bellman-Ford algorithm can handle graphs with negative weight edges, unlike Dijkstra's algorithm.